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A Clustering Approach to Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-hop Relay Networks Yang Yu, Seán Murphy, Liam Murphy Department of Computer Science and Informatics University College Dublin, Ireland Abstract - In this paper, a clustering approach to solve a network planning problem for 802.16j relay networks is considered. Our clustering approach consists of three basic steps: (1) divide the nodes into k distinct clusters, (2) solve the planning problem separately for each cluster, and (3) perform a final optimization to reduce issues arising at cluster boundaries. Simulation results show that our approach is more efficient than existing approaches: solutions of equivalent quality can be found in 40% of the time. Thus our technique can be used to solve larger problems with similar hardware, or similar size problems in less time.

I.

INTRODUCTION

Activity in the WiMAX community continues apace: products are reaching the market, networks are being rolled out and service offerings are in their early stages. The community is an area which continues to innovate in many ways, one of which is the development of new standards to solve open problems. One such initiative which is receiving much interest right now is the development of the multi-hop relay standard, 802.16j. This standard is being developed to provide low cost coverage in the initial stages of network deployment and increased capacity when there is higher utilisation of the network. A fundamental assumption being made in this work is that the relays can be developed at significantly lower cost than Base Stations (BSs). This standard is expected to have significant impact in new 802.16 rollouts. This is important, as there are many parts of the world where the business case for WiMax rollout is not so compelling and/or the regulatory authorities have not approved the technology/spectrum for use in a mobile context. For these cases, where network rollout has not yet occurred, providing a lower cost coverage solution is very attractive. While relay technologies are not an entirely new concept, large-scale deployment of standardised relay-based technology is new. Hence, there is a need for new approaches to network planning to obtain solutions for operators considering how to roll-out a relay-based solution. This paper is a development of earlier work by the authors [1] in which an Integer Programming problem formulation was developed and standard branch and bound techniques were used to obtain solutions. In that work, it was found that the standard approaches can be used to solve problems of small

metropolitan scale: here, we investigate approaches which are more scalable. The rest of the paper is organised as follows. Section II discusses related work. In Section III, the problem formulation is developed. This section also discusses approaches to solving this problem including a clustering model. In Section IV, some results are presented which focus on the performance of the different solution approaches. Finally, Section V contains the conclusion of the paper. II.

RELATED WORKS

802.16 standards have been under development since 1998, with the development of the first standard for last-mile Fixed Wireless Access in 2001 [2, 3]. The initial standard had significant limitations: it was focused on high frequency operation and did not provide mobility support. The development of 802.16a and subsequently, 802.16-2004 supported operation in lower frequency bands (2-11GHz) and the ratification of 802.16e in 2005 provided support for mobility. 802.16j is a more recent initiative which is focused on developing low-cost relay architectures for 802.16 systems. It has passed the initial stages of its work – the requirements have been identified and some key characteristics of the solution are reaching consensus: however, there is much left to do. Despite this, it is possible to consider network planning for 802.16j systems as it necessitates making an abstraction of the system which can be done even though many details of the system operation are not yet agreed upon. Network planning problems have been well studied for different types of wireless networks. In [4], the authors focus on planning of 3G cellular networks. So-called static Test Points (TPs) are used to characterise the user demand on the network; areas which generate more traffic have a higher density of test points. An Integer Programming formulation is developed and a number of approaches based on greedy algorithms and tabu search are investigated to determine good locations for the BSs. In [5], the authors consider the use of clustering techniques to solve WCDMA planning problems. Our work uses similar techniques, albeit in a different context. In [7] and [8], a heuristic algorithm was developed to determine the cell sites selection problem during upgrading from 2G to 3G. The objective was to determine a solution which minimised cell count and associated costs while continuing to satisfy the user demand during the upgrade.

While 3G network planning has been well studied, the base radio technology on which it is based differs from that of 802.16: for this reason, new approaches to planning 802.16 networks are necessary. In [9], the authors focus on 802.16 overlay networks. They develop an Integer Programming problem formulation and propose some heuristic algorithms to solve the problem. More typical cellular planning approaches are considered in [10] and [11]. Paper [10] focuses on the design of a Point to Multi-Point (PMP) system in Portugal, while [11] considers a similar problem in Athens, although both approaches can, of course, be applied in other contexts. Both approaches took carrier to noise ratio, carrier to interference ratio and geographical information into account. While these reports describe interesting work in the context of planning current 802.16 networks, they cannot be used to solve problems associated with relay-based networking. The closest published work to that described here was contributed by Hoymann et al in a two companion papers [11, 12]. In [12] the authors use sophisticated radio models to determine inter-cell interference, CINR (Carrier to Interference and Noise Ratios) and uplink and downlink throughput for different network configurations. The work described in [13] is a development of the earlier work which considers the multihop case. The authors focus on small number of neighbouring systems but not the network perspective view. Their contribution is important and is a natural complement to this work, although the scenarios that they focus on differ a little in terms of the radio technology used. III.

PLANNING MODEL

Here, a specific problem formulation for planning of multihop 802.16 networks is developed. The following inputs are assumed: • a set of candidate BS and RS sites; • user demand, modelled by a set of discrete Test Points (TPs); • a suitable propagation model; • a set of costs associated with BS and RS. The objective is to determine the set of BSs and RSs that can accommodate the user demand at lowest cost. In any wireless network planning problem, the radio model is a key component. In general, radio models can be almost arbitrarily complex. Working with such models, it is important to find right level of abstraction, i.e. few characteristics captured may result in less computational time but poor result and in contrast too many characteristics captured may result in accurate result but very high computational complexity. The propagation model used here is the well-known SUI channel model which is recommended by IEEE 802.16 work group [14]. To use the model, it is necessary to define a number of parameters: terrain type, frequency of operation, antenna height, etc. In the experiments described below a single set of parameters were used as in Table I.

TABLE I PARAMETERS USED IN SUI MODEL Parameter Name

Value

Height of BSs and RSs Height of TPs Frequency

Random value between 10~80m 1.6m 2.5GHz C, mostly flat terrain with light tree densities

Terrain Type

The problem formulation and the state space reduction have been stated in [1] and are briefly presented in III.A and III.B below. A clustering approach to solve the problem is then described in III.C. A. Problem Formulation The following problem inputs are defined: • • • • • • (

S = {1, … , m}: Set of candidate site for BSs; R = {1, … , n}: Set of candidate site for RSs; T = {1, … , t}: Set of TPs;
 : Cost of BS j, (  );
 : Cost of RS j, (  ); : Traffic demand (number of connections) for TP i,  )

•

∑  

is the average traffic demand for all TPs.

In this paper, the multi-hop concept is limited to nodes which are at most two hops from the BS: hence Subscriber Stations (SSs) can connect to an RS which is connected to the BS, or they can connect directly to the BS. The gain matrices are determined based on the SUI model:

  •   (0